Jianxiong Xiao

Position Opening:

For prospective graduate students (both PhD and Master): There will be opening in our group each year. You are required to apply via the department's system. *There is no need to email me. Contacting me without a good reason will NOT help. If you want to email me because of a special reason, please include [Prospective Graduate Student with Special Questions] in your email title.*
You can *indicate your interest to work in our group in your application form* and we will review your materials.
There is no requirement for previous research experience or publication in computer vision, but strong interest and solid programming skill is required.
To demonstrate your programming skill, you can put the source code and demo videos online for the systems that you build,
and put a link to them in your CV or research statement.
If you have questions about the graduate program admissions process or requirements, please see the department’s information here.

For Princeton undergrad students,
you are welcome to work with us for independent work or senior thesis.
Contact me by email with your GPA.

Brief Bio:

Jianxiong Xiao is an Assistant Professor in the Department of Computer Science at Princeton University. He received his Ph.D. from the Computer Science and Artificial Intelligence Laboratory (CSAIL) at Massachusetts Institute of Technology (MIT). His research interests are in computer vision, with a focus on data-driven scene understanding. He has been motivated by the goal of building computer systems that automatically understand visual scenes, both inferring the semantics (e.g. SUN Database) and extracting 3D structure (e.g. Big Museum). His work has received the Best Student Paper Award at the European Conference on Computer Vision (ECCV) in 2012 and Google Research Best Papers Award for 2012, and has appeared in popular press in the United States. Jianxiong was awarded the Google U.S./Canada Fellowship in Computer Vision in 2012, MIT CSW Best Research Award in 2011, and two Google Research Awards in 2014 and in 2015.
More information can be found at: http://vision.princeton.edu.